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biological organs
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Conductivity, Frequency-domain analysis, Image reconstruction,
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Gong, B.,
Schullcke, B.,
Krueger-Ziolek, S.,
Vauhkonen, M.,
Wolf, G.,
Mueller-Lisse, U.,
Moeller, K.,
EIT Imaging Regularization Based on Spectral Graph Wavelets,
MedImg(36), No. 9, September 2017, pp. 1832-1844.
IEEE DOI
1709
bioelectric phenomena, biological tissues,
electric impedance imaging,
wavelet transforms, wavelet transforms, Jacobian matrices,
Electricalimpedancetomography
BibRef
Liu, D.,
Khambampati, A.K.,
Du, J.,
A Parametric Level Set Method for Electrical Impedance Tomography,
MedImg(37), No. 2, February 2018, pp. 451-460.
IEEE DOI
1802
Conductivity, Image reconstruction, Inverse problems, Level set,
Lungs, Shape, Tomography, Electrical impedance tomography,
parametric level set method
BibRef
Garmatter, D.[Dominik],
Harrach, B.[Bastian],
Magnetic Resonance Electrical Impedance Tomography (MREIT):
Convergence and Reduced Basis Approach,
SIIMS(11), No. 1, 2018, pp. 863-887.
DOI Link
1804
BibRef
Liu, S.,
Jia, J.,
Zhang, Y.D.,
Yang, Y.,
Image Reconstruction in Electrical Impedance Tomography Based on
Structure-Aware Sparse Bayesian Learning,
MedImg(37), No. 9, September 2018, pp. 2090-2102.
IEEE DOI
1809
Tomography, Image reconstruction, Bayes methods, Electrodes,
Voltage measurement, Conductivity, Computational modeling,
maximuma posteriori(MAP) estimation
BibRef
Leijsen, R.L.,
Brink, W.M.,
van den Berg, C.A.T.,
Webb, A.G.,
Remis, R.F.,
3-D Contrast Source Inversion-Electrical Properties Tomography,
MedImg(37), No. 9, September 2018, pp. 2080-2089.
IEEE DOI
1809
Radio frequency, Mathematical model,
Image reconstruction, Magnetic resonance imaging,
electromagnetic Green's tensor field representations
BibRef
Lee, K.,
Woo, E.J.,
Seo, J.K.,
A Fidelity-Embedded Regularization Method for Robust Electrical
Impedance Tomography,
MedImg(37), No. 9, September 2018, pp. 1970-1977.
IEEE DOI
1809
Electrodes, Conductivity, Tomography, Image reconstruction,
Voltage measurement, Jacobian matrices,
motion artifacts reduction
BibRef
Hamilton, S.J.,
Hauptmann, A.,
Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With
Deep Neural Networks,
MedImg(37), No. 10, October 2018, pp. 2367-2377.
IEEE DOI
1810
Tomography, Image reconstruction, Conductivity, Real-time systems,
Impedance, Robustness, Current measurement,
conductivity imaging
BibRef
Liu, D.,
Smyl, D.,
Du, J.,
A Parametric Level Set-Based Approach to Difference Imaging in
Electrical Impedance Tomography,
MedImg(38), No. 1, January 2019, pp. 145-155.
IEEE DOI
1901
Conductivity, Tomography, Image reconstruction,
Computational modeling, Level set, Conductivity measurement,
inverse problems
BibRef
Liu, D.,
Gu, D.,
Smyl, D.,
Deng, J.,
Du, J.,
B-Spline Level Set Method for Shape Reconstruction in Electrical
Impedance Tomography,
MedImg(39), No. 6, June 2020, pp. 1917-1929.
IEEE DOI
2006
Electrical impedance tomography, B-spline level set method,
Inverse problems, Shape reconstruction
BibRef
Liu, D.,
Gu, D.,
Smyl, D.,
Deng, J.,
Du, J.,
Shape Reconstruction Using Boolean Operations in Electrical Impedance
Tomography,
MedImg(39), No. 9, September 2020, pp. 2954-2964.
IEEE DOI
2009
Shape, Image reconstruction, Conductivity, Splines (mathematics),
Level set, Reconstruction algorithms,
lung imaging
BibRef
Ren, S.,
Sun, K.,
Liu, D.,
Dong, F.,
A Statistical Shape-Constrained Reconstruction Framework for
Electrical Impedance Tomography,
MedImg(38), No. 10, October 2019, pp. 2400-2410.
IEEE DOI
1910
Shape, Lung, Image reconstruction, Computed tomography, Conductivity,
Electrical impedance tomography, lung imaging,
robust principal component analysis
BibRef
Liu, D.,
Gu, D.,
Smyl, D.,
Deng, J.,
Du, J.,
B-Spline-Based Sharp Feature Preserving Shape Reconstruction Approach
for Electrical Impedance Tomography,
MedImg(38), No. 11, November 2019, pp. 2533-2544.
IEEE DOI
1911
Tomography, Splines (mathematics), Shape, Image reconstruction,
Conductivity, Fourier series, Numerical models,
inverse problems
BibRef
Liu, D.,
Du, J.,
A Moving Morphable Components Based Shape Reconstruction Framework
for Electrical Impedance Tomography,
MedImg(38), No. 12, December 2019, pp. 2937-2948.
IEEE DOI
1912
Shape, Image reconstruction, Tomography, Topology, Level set,
Conductivity, Electrodes, Electrical impedance tomography,
inverse problems
BibRef
Jiang, Y.D.,
Soleimani, M.,
Capacitively Coupled Electrical Impedance Tomography for Brain
Imaging,
MedImg(38), No. 9, September 2019, pp. 2104-2113.
IEEE DOI
1909
Electrodes, Tomography, Impedance, Head, Conductivity,
Electrical resistance measurement,
multi-frequency time-difference imaging
BibRef
Connell, I.R.O.,
Menon, R.S.,
Shape Optimization of an Electric Dipole Array for 7 Tesla
Neuroimaging,
MedImg(38), No. 9, September 2019, pp. 2177-2187.
IEEE DOI
1909
Radio frequency, Optimization, Conductors, Shape, Head, Couplings,
Impedance, Radio-frequency arrays, RF arrays, MRI RF coils, dipoles,
shape optimization
BibRef
Liang, G.,
Ren, S.,
Dong, F.,
A Shape-Based Statistical Inversion Method for EIT/URT Dual-Modality
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2002
Dual-modality imaging, inclusion boundary reconstruction,
electrical impedance tomography,
statistical inversion
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Wei, Z.,
Chen, X.,
Induced-Current Learning Method for Nonlinear Reconstructions in
Electrical Impedance Tomography,
MedImg(39), No. 5, May 2020, pp. 1326-1334.
IEEE DOI
2005
Tomography, Conductivity, Mathematical model, Image reconstruction,
Inverse problems, Pollution measurement, Electrodes,
convolutional neural network
BibRef
Li, Z.,
Zhang, J.,
Liu, D.,
Du, J.,
CT Image-Guided Electrical Impedance Tomography for Medical Imaging,
MedImg(39), No. 6, June 2020, pp. 1822-1832.
IEEE DOI
2006
Computed tomography, cross-gradient function,
electrical impedance tomography, lung imaging
BibRef
Jauhiainen, J.[Jyrki],
Kuusela, P.[Petri],
Seppänen, A.[Aku],
Valkonen, T.[Tuomo],
Relaxed Gauss-Newton Methods with Applications to Electrical
Impedance Tomography,
SIIMS(13), No. 3, 2020, pp. 1415-1445.
DOI Link
2010
BibRef
Murphy, E.K.,
Wu, X.,
Everitt, A.C.,
Halter, R.J.,
Phantom Studies of Fused-Data TREIT Using Only Biopsy-Probe
Electrodes,
MedImg(39), No. 11, November 2020, pp. 3367-3378.
IEEE DOI
2011
Electrodes, Biopsy, Probes, Tomography, Image reconstruction,
Conductivity, Data fusion, electrical impedance tomography,
bioimpedance
BibRef
Li, X.,
Lu, Y.,
Wang, J.,
Dang, X.,
Wang, Q.,
Duan, X.,
Sun, Y.,
An image reconstruction framework based on deep neural network for
electrical impedance tomography,
ICIP17(3585-3589)
IEEE DOI
1803
Conductivity, Finite element analysis, Image reconstruction,
Mathematical model, Tomography, Training, Voltage measurement,
stacked autoencoder (SAE)
BibRef
Zaravi, S.,
Amirfattahi, R.,
Vahdat, B.V.,
Investigation of error propagation and measurement error for 2D block
method in Electrical Impedance Tomography,
IPRIA15(1-4)
IEEE DOI
1603
bioelectric potentials
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Lu, L.[Lin],
Liu, L.[Lili],
Hu, C.[Chun],
Analysis of the electrical impedance tomography algorithm based on
finite element method and Tikhonov regularization,
ICWAPR14(36-42)
IEEE DOI
1402
Electrodes
BibRef
Maimaitijiang, Y.,
Roula, M.A.,
Sobeihi, K.,
Watson, S.,
Williams, R.J.,
Griffiths, H.,
A parallel implementation of a Magnetic Induction Tomography: Image
reconstruction algorithm on the ClearSpeed Advance accelerator board,
ICIP09(1757-1760).
IEEE DOI
0911
BibRef
Isa, M.D.[Mohd Daud],
Rahmat, M.F.[Mohd Fua'ad],
Application of Digital Imaging Technique in Electrical Charge
Tomography System for Image Reconstruction Validation,
ICMV09(277-281).
IEEE DOI
0912
BibRef
He, S.J.[Shi-Jun],
Wang, H.X.[Hua-Xiang],
Zhou, R.Y.[Ru-Yan],
A 3D Image Reconstruction Algorithm of Electrical Capacitance
Tomography Based on Support Vector Machines,
CISP09(1-4).
IEEE DOI
0910
BibRef
Huang, J.J.[Ji-Jer],
Cheng, K.S.[Kuo-Sheng],
The effect of electrode-skin interface model in electrical impedance
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ICIP98(III: 837-840).
IEEE DOI
9810
BibRef
Martin, T.,
Idier, J.,
A FEM-Based Nonlinear MAP Estimator in Electrical Impedance
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ICIP97(II: 684-687).
IEEE DOI
BibRef
9700
Shallof, A.M.,
Barber, D.C.,
Imaging the complex conductivity in electrical impedance tomography,
ICIP96(III: 543-546).
IEEE DOI
9610
BibRef
Gu, T.Y.[Tian-You],
Wu, B.Y.[Bao-Yong],
Zhang, C.L.[Cheng-Lin],
Zhang, D.C.[Dian-Cheng],
An experimental system for the waveform recognition of impedance
plethysmography,
ICPR88(I: 473-475).
IEEE DOI
8811
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tomographic Image Generation, Cone-Beam, Fan-Beam, Helical, Spiral Reconstruction .